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Maximum power point tracking of PEMFC based on hybrid artificial bee colony algorithm with fuzzy control
Maximum power point tracking (MPPT) is an effective method to improve the power generation efficiency and power supply quality of a proton exchange membrane fuel cell (PEMFC). Due to the inherent nonlinear characteristics of PEMFC, conventional MPPT methods are often difficult to achieve a satisfact...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8918329/ https://www.ncbi.nlm.nih.gov/pubmed/35279691 http://dx.doi.org/10.1038/s41598-022-08327-5 |
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author | Fan, Liping Ma, Xianyang |
author_facet | Fan, Liping Ma, Xianyang |
author_sort | Fan, Liping |
collection | PubMed |
description | Maximum power point tracking (MPPT) is an effective method to improve the power generation efficiency and power supply quality of a proton exchange membrane fuel cell (PEMFC). Due to the inherent nonlinear characteristics of PEMFC, conventional MPPT methods are often difficult to achieve a satisfactory control effect. Considering this, artificial bee colony algorithm combining fuzzy control (ABC-fuzzy) was proposed to construct a MPPT control scheme for PEMFC. The global optimization ability of ABC algorithm was used to approach the maximum power point of PEMFC and solve the problem of falling into local optimization, and fuzzy control was used to eliminate the problems of large overshoot and slow convergence speed of ABC algorithm. The testing results show that compared with perturb & observe algorithm, conductance increment and ABC methods, ABC-fuzzy method can make PEMFC obtain greater output power, faster regulation speed, smaller steady-state error, less oscillation and stronger anti-interference ability. The MPPT scheme based on ABC-fuzzy can effectively realize the maximum power output of PEMFC, and plays an important role in improving the service life and power supply efficiency of PEMFC. |
format | Online Article Text |
id | pubmed-8918329 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89183292022-03-16 Maximum power point tracking of PEMFC based on hybrid artificial bee colony algorithm with fuzzy control Fan, Liping Ma, Xianyang Sci Rep Article Maximum power point tracking (MPPT) is an effective method to improve the power generation efficiency and power supply quality of a proton exchange membrane fuel cell (PEMFC). Due to the inherent nonlinear characteristics of PEMFC, conventional MPPT methods are often difficult to achieve a satisfactory control effect. Considering this, artificial bee colony algorithm combining fuzzy control (ABC-fuzzy) was proposed to construct a MPPT control scheme for PEMFC. The global optimization ability of ABC algorithm was used to approach the maximum power point of PEMFC and solve the problem of falling into local optimization, and fuzzy control was used to eliminate the problems of large overshoot and slow convergence speed of ABC algorithm. The testing results show that compared with perturb & observe algorithm, conductance increment and ABC methods, ABC-fuzzy method can make PEMFC obtain greater output power, faster regulation speed, smaller steady-state error, less oscillation and stronger anti-interference ability. The MPPT scheme based on ABC-fuzzy can effectively realize the maximum power output of PEMFC, and plays an important role in improving the service life and power supply efficiency of PEMFC. Nature Publishing Group UK 2022-03-12 /pmc/articles/PMC8918329/ /pubmed/35279691 http://dx.doi.org/10.1038/s41598-022-08327-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Fan, Liping Ma, Xianyang Maximum power point tracking of PEMFC based on hybrid artificial bee colony algorithm with fuzzy control |
title | Maximum power point tracking of PEMFC based on hybrid artificial bee colony algorithm with fuzzy control |
title_full | Maximum power point tracking of PEMFC based on hybrid artificial bee colony algorithm with fuzzy control |
title_fullStr | Maximum power point tracking of PEMFC based on hybrid artificial bee colony algorithm with fuzzy control |
title_full_unstemmed | Maximum power point tracking of PEMFC based on hybrid artificial bee colony algorithm with fuzzy control |
title_short | Maximum power point tracking of PEMFC based on hybrid artificial bee colony algorithm with fuzzy control |
title_sort | maximum power point tracking of pemfc based on hybrid artificial bee colony algorithm with fuzzy control |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8918329/ https://www.ncbi.nlm.nih.gov/pubmed/35279691 http://dx.doi.org/10.1038/s41598-022-08327-5 |
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